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He was most interested in the continuing evolution of their concept of time, their efforts at universal forms of communication through their modern computer networks, and their search for a unifying force behind what they call the four fundamental forces of nature: gravity, electromagnetism, and the strong and weak nuclear forces In attempting to share any new insights with them, he knew he was facing an uphill struggle.

5 sale_day INT NOT NULL) 6 PARTITION BY HASH (ticket_no) 7 PARTITIONS 4 8* STORE IN (ts1,ts2,ts3,ts4); Table created. SQL> In the preceding example, four hash partitions are created in four tablespaces. We won t know in which partition the data for, say, June 10, 2008, is stored. Oracle determines the storage based on a hashing algorithm, and you have no control whatsoever over the row-to-partition mapping.

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among the components and any constraints that exist. Conceptual modeling of the enterprise leads to clear indications regarding the tables to be built later on and the relationships that should exist among those tables. ER modeling involves the creation of valid models of the business, using standard entity-relationship diagrams (ERDs). Note that the conceptual model is always independent of both software and hardware considerations. ER modeling was originally proposed by Peter Chen in 1976, and it is now the most widely used technique for database design. (You can download Chen s original proposal document as a PDF file at http://bit.csc.lsu.edu/~chen/pdf/erd.pdf.) Nevertheless, there are several design methodologies other than ER modeling available for you to use. For several years, researchers have struggled to model the real world more realistically by using semantic data models, which try to go beyond the traditional ER modeling methodology.

There may be times when you ll want to partition the data not on the basis of a time range or evenly distributed hashing scheme, but rather by known values, such as city, territory, or some such attribute. List partitioning is preferable to range or hash partitioning when your data is distributed among a set number of discrete values. For example, you may want to group a company s sales data according to regions rather than quarters. List partitioning enables you to group your data on the same lines as real-world groupings of data, rather than arbitrary ranges of time or some such criterion. For example, when you re dealing with statewide totals in the United States, you ll be dealing with 50 different sets of data. It makes more sense in this situation to partition your data into four or five regions, rather than use the range method to partition the data alphabetically. Listing 7-6 shows how to use list partitioning to partition the ticket_sales table. The partitions are made up of groups of flight-originating cities, shown by the start_city column. Listing 7-6. Creating a List-Partitioned Table SQL> 2 3 4 5 6 7 8 9 10 11 12* CREATE TABLE sales_data (ticket_no NUMBER, sale_year INT NOT NULL, sale_month INT NOT NULL, sale_day INT NOT NULL, destination_city CHAR(3), start_city CHAR(3)) PARTITION BY LIST (start_city) (PARTITION northeast_sales values ('NYC','BOS','PEN') TABLESPACE ts1, PARTITION southwest_sales values ('DFW','ORL','HOU') TABLESPACE ts2, PARTITION pacificwest_sales values('SAN','LOS','WAS') TABLESPACE ts3, PARTITION southeast_sales values ('MIA','CHA','ATL') TABLESPACE ts4);

The World Wide Web Consortium (W3C) is working on a specification related to data representation on the Internet. The general idea is to try to bring some meaning to the massive amount of data and information available. Information on the Web is designed for and presented to humans, but on the semantic Web, data and information will be designed so that it can be understood and manipulated by computers as well as humans. On the semantic Web, you will use software agents to go off in search of data and information on your behalf. An excellent article on this new and exciting approach is The Semantic Web, by Tim Berners-Lee, James Hendler, and Ora Lassila, available at http://www.scientificamerican.com/article.cfm articleID=00048144-10D21C70-84A9809EC588EF21&catID=2.

Table created. SQL> In the previous list-partitioning example, the partition description specifies a list of values for the start_city column. Our table creation statement created four list partitions. Only cities that fall in this list will be included in the partition. A ticket with the information 9999, 2004, 06, 01, DFW, HOU will be stored in the southwest_sales partition.

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